Reviewing Intelligent Cinematography: AI research for camera-based video production
arxiv(2024)
摘要
This paper offers a comprehensive review of artificial intelligence (AI)
research in the context of real camera content acquisition for entertainment
purposes and is aimed at both researchers and cinematographers. Considering the
breadth of computer vision research and the lack of review papers tied to
intelligent cinematography (IC), this review introduces a holistic view of the
IC landscape while providing the technical insight for experts across across
disciplines. We preface the main discussion with technical background on
generative AI, object detection, automated camera calibration and 3-D content
acquisition, and link explanatory articles to assist non-technical readers. The
main discussion categorizes work by four production types: General Production,
Virtual Production, Live Production and Aerial Production. Note that for
Virtual Production we do not discuss research relating to virtual content
acquisition, including work on automated video generation, like Stable
Diffusion. Within each section, we (1) sub-classify work by the technical field
of research - reflected by the subsections, and (2) evaluate the trends and
challenge w.r.t to each type of production. In the final chapter, we present
our concluding remarks on the greater scope of IC research and outline work
that we believe has significant potential to influence the whole industry. We
find that work relating to virtual production has the greatest potential to
impact other mediums of production, driven by the growing interest in LED
volumes/stages for in-camera virtual effects (ICVFX) and automated 3-D capture
for a virtual modelling of real world scenes and actors. This is the first
piece of literature to offer a structured and comprehensive examination of IC
research. Consequently, we address ethical and legal concerns regarding the use
of creative AI involving artists, actors and the general public, in the...
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